Generating consolidated social content for a user of a social networking system

ABSTRACT

To generate dynamic relationship-based content personalized for members of a social networking system, at least one action of one or more members of the social networking system is associated with relationship data for the one or more members to produce consolidated data. One or more elements associated with the consolidated data is identified and used to aggregate the consolidated data. Further exemplary methods comprise weighting by affinity the aggregated consolidated data to generate dynamic relationship-based content personalized for the members of the web-based social network.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. application Ser. No.13/962,897, filed Aug. 8, 2013, which is a continuation of U.S.application Ser. No. 12/902,024, filed Oct. 11, 2010, now issued as U.S.Pat. No. 8,521,787, which is a continuation of U.S. application Ser. No.11/502,757, filed Aug. 11, 2006, now issued as U.S. Pat. No. 7,827,208,each of which are incorporated by reference in their entirety.

BACKGROUND

The present invention relates generally to social networking, and moreparticularly to systems and methods for generating dynamicrelationship-based content personalized for members of a web-basedsocial network.

As social networking has grown more popular, the information availableto each member has become voluminous. Accordingly, members may beinundated with information that does not interest the members. Further,members may find themselves unable to find in a timely and efficientmanner the information that does interest them, such as informationabout their friends and their community. There is therefore a need forsystems and methods for generating dynamic relationship-based contentpersonalized for members of a web-based social network.

SUMMARY

Systems and methods for generating dynamic relationship-based contentpersonalized for members of a web-based social network are provided. Anexemplary method comprises storing at least one action of one or moremembers of a web-based social network, accessing relationship data forthe one or more members, associating the at least one action with therelationship data to produce consolidated data, identifying one or moreelements associated with the consolidated data, and aggregating theconsolidated data based on the one or more elements to produceaggregated consolidated data. Further exemplary methods compriseweighting by affinity the aggregated consolidated data to generatedynamic relationship-based content personalized for the members of theweb-based social network.

An exemplary system for generating dynamic relationship-based contentpersonalized for members of a web-based social network comprises adatabase configured for storing at least one action of one or moremembers of a web-based social network, a database configured withrelationship data for the one or more members of the web-based socialnetwork, a processing module configured with an association component toassociate the at least one action with the relationship data to produceconsolidated data, the processing module configured with anidentification component to identify one or more elements associatedwith the consolidated data, and the processing module configured with anaggregation component to aggregate the consolidated data based on theone or more elements to produce aggregated consolidated data. A furtherexemplary system comprises the processing module configured with anaffinity component to weight by affinity the aggregated consolidateddata to generate dynamic relationship-based content personalized for themembers of the web-based social network.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates an exemplary environment for generating dynamicrelationship-based content personalized for members of a web-basedsocial network.

FIG. 2 is a block diagram of an exemplary content engine.

FIG. 3 is a block diagram of an exemplary processing module.

FIG. 4 is an exemplary screen shot of items of generated dynamicrelationship-based content personalized for a member of a web-basedsocial network.

FIG. 5 is a flow diagram of an exemplary process for generating dynamicrelationship-based content personalized for members of a web-basedsocial network.

The figures depict various embodiments of the present invention forpurposes of illustration only. One skilled in the art will readilyrecognize from the following discussion that alternative embodiments ofthe structures and methods illustrated herein may be employed withoutdeparting from the principles of the invention described herein.

DETAILED DESCRIPTION

Systems and methods for generating dynamic relationship-based contentpersonalized for members of a web-based social network are provided. Atleast one action of one or more members of a web-based social network isassociated with relationship data for the one or more members to produceconsolidated data. One or more elements associated with the consolidateddata are identified and used to aggregate the consolidated data. Furtherexemplary methods comprise weighting by affinity the aggregatedconsolidated data to generate dynamic relationship-based contentpersonalized for the members of the web-based social network.

FIG. 1 illustrates an exemplary environment for generating dynamicrelationship-based content personalized for members of a web-basedsocial network. One or more members, such as a member at a member device102, are coupled to a web-based social network 106 via a network 104.

The web-based social network 106 may comprise any entity that providessocial networking services, communication services, dating services, andso forth. For example, the web-based social network 106 may host awebsite that allows one or more members, such as the member at themember device 102, to communicate with one another via the website. Inone instance, a first member associated with the member device 102 maycommunicate with one or more second members associated with one or moresecond member devices via a social networking website associated withthe web-based social network 106. The social networking website offersthe member an opportunity to connect or reconnect with the one or moresecond members that attended, for example, the same university as themember.

According to exemplary embodiments, one or more networks or communitiesmay be provided for each member. For example, the member may have anetwork comprised of people grouped according to a university attended,a network comprised of people grouped according to the member'sgeographical location of residence, a network comprised of peoplegrouped according to a common field of work, a network comprised ofpeople grouped according to a particular business, and so forth.

A content engine 108 is coupled to the web-based social network 106. Thecontent engine 108 utilizes action and relationship data about the oneor more members, such as the member at the member device 102, togenerate dynamic relationship-based content personalized for members ofthe web-based social network 106. According to some embodiments, themember device 102 may be directly coupled to the content engine 108.According to other embodiments, the content engine 108 comprises amodule associated with the web-based social network 106.

Referring now to FIG. 2, a block diagram of an exemplary content engineis shown. Exemplary content engine 108 comprises an action database 202,relationship database 204, processing module 206, storage database 208,and publisher 210.

An action database 202 may store one or more member actions oractivities on the web-based social network 106 (FIG. 1). For example,the action database 202 may store member actions with one or more itemsof content, such as news stories, other members' profiles, and/or emailprovided via the web-based social network 106. Any type of member actionmay be stored in the action database 202.

According to exemplary embodiments, action data may represent aparticular member's actions on the web-based social network 106 for aparticular period of time, such as the most recent hour, six hours, day,week or month. For example, Member A's action data may represent MemberA's actions for the last hour of sending an email to another member,electing to attend a concert with three other members, and adding aphoto to Member A's profile.

A relationship database 204 is provided for storing relationship dataassociated with each of the members, such as the member associated withthe member device 102 (FIG. 1). According to exemplary embodiments,relationship database 204 comprises a member profile for each member ofthe web-based social network 106. When a member joins web-based socialnetwork 106, a member profile may be generated for the member. Themember can specify relationships with one or more other members via themember profile, or by any other means. The member can assign categories,groups, networks, and so forth to the one or more other members withwhich the member has a relationship. The relationship, for example, mayspecify that the member is a friend, friend of a friend, family member,schoolmate, ex-girlfriend, and so forth. Any type of relationship may bespecified. Further, the member may group other members according to oneor more categories. When the member updates information in the memberprofile, such as adding additional contacts or friends, the memberprofile in the relationship database 204 may be updated with theinformation added.

According to some embodiments, processing module 206 is provided forperforming several functions as described herein in connection with FIG.3. Among other things, processing module 206 is responsible forassociating member actions with member relationship data to produceconsolidated data. Processing module 206 identifies one or more elementsassociated with the consolidated data and aggregates the consolidateddata based on the one or more elements to produce aggregatedconsolidated data. In a further embodiment, processing module 206weights by affinity the aggregated consolidated data to generate dynamicrelationship-based content personalized for the members of the web-basedsocial network 106. Storage database 208 may be provided for storing thegenerated dynamic relationship-based content personalized for themembers of the web-based social network 106.

Publisher 210 may be provided for publishing the generated dynamicrelationship-based content personalized for the members of the web-basedsocial network 106. According to one embodiment, publisher 210 comprisesa server configured to send the generated dynamic relationship-basedcontent to a member for whom the content has been personalized. In afurther embodiment, publisher 210 is configured to format content in apredetermined arrangement style for presentation to the member of theweb-based social network 106.

Although the exemplary content engine 108 is described as beingcomprised of various components (the action database 202, therelationship database 204, processing module 206, storage database 208,and publisher 210), fewer or more components may comprise the contentengine 108 and still fall within the scope of various embodiments.

FIG. 3 is a block diagram of an exemplary processing module. Asdescribed in connection with FIG. 2, according to one embodiment,processing module 206 comprises an association component 302, anidentification component 304, an aggregation component 306, and anaffinity component 308.

Association component 302 is configured to associate one or more memberactions with the member's relationship data to produce consolidateddata. For example, Member A's profile may include fifteen friends ofMember A and another twenty friends of Member A's friends (“friends offriends”). Association component 302 will associate Member A's actionswith Member A's friends, friends of friends, and/or other members. Forinstance, association component 302 might associate Member A's action ofjoining a group dedicated to the band “Green Day” with Member A'sfriends who also belong to the same group. In this example, the producedconsolidated data might be in the form of “Member A joins Green DayGroup, which also includes Member A's friends Pete and Bill.”

An identification component 304 may be provided as part of processingmodule 206 to identify one or more elements associated with theconsolidated data. For example, with respect to consolidated data in theform of “Member A joins Green Day Group, which also includes Member A'sfriends Pete and Bill,” identification component 304 might identify theelements of “Green Day.” According to some embodiments, identificationcomponent 304 may identify any element of an action associated withrelationship data (to form consolidated data). For example,identification component 304 may identify an element based on actiontype, members involved, media or content type, and/or multiple elementsthereof The identified elements are used to aggregate consolidated data,as described herein.

According to some embodiments, aggregation component 306 is provided toaggregate the consolidated data based on the one or more elements toproduce aggregated consolidated data. For example, aggregation component306 might utilize the elements of “Green Day” to aggregate theconsolidated data of “Member A joins Green Day Group, which alsoincludes Member A's friends Pete and Bill,” with other consolidated datasharing the same elements of “Green Day.” In this example, aggregationby aggregation component 306 might result in aggregated consolidateddata in the form of “Member A and fifty other members of Member A'scommunity join the Green Day Group.” Aggregation component 306 mayutilize other parameters or criteria for aggregation and remain withinthe scope of embodiments claimed herein.

According to some embodiments, affinity component 308 is provided toweight by affinity the aggregated consolidated data to generate dynamicrelationship-based content personalized for members of web-based socialnetwork 106. Based on one or more member activities and associatedrelationships, an affinity for past, present, or future content may bedetermined by the affinity component 308. Any type of variable may beconsidered when determining an affinity for the affinity component 308to weight the aggregated consolidated data. In a further embodiment,affinity component 308 may be utilized to assign an order to the contentpresented to the member. For example, a story about Member B breaking upwith Member C may be rated lower than a story about Member A's brotherhaving a baby, and accordingly, the story about Member B breaking upwith Member C may appear below the story about Member A's brother havinga baby.

FIG. 4 is an exemplary screen shot of items of generated dynamicrelationship-based content personalized for a member of a web-basedsocial network. The exemplary screen shot 400 represents the displaypage associated with a particular member, such as the member at memberdevice 102. Various stories, content, and so forth may be displayed viathe display page. In the exemplary screen shot shown in FIG. 4, severalstories and/or story headlines are displayed.

A first story 402, entitled “Dana joined the group Who is Myke Jones?”is rated highest according to affinity. An affinity may have beenassigned to each story appearing on the display page, based on themember's interaction with other content and the member's relationshipsassociated with the member's interaction with the other content. Thestories are then displayed in an order according to the affinity. Forexample, the first story 402 is assigned the highest order based on theaffinity determined for the member for content and/or other membersincluded in the first story 402, while a second story 404, entitled“Anthony joined the group Pugs? Yes, please!”, is assigned the secondhighest order based on the affinity determined for the member withrespect to the content and/or the other members included in the secondstory 404, and so forth.

Although the affinity is determined based on the one or more memberactivities within the web-based social network 106, according to someembodiments, member activity outside of the web-based social network 106may also be considered in determining affinity for content and/or othermembers.

Referring now to FIG. 5, a flow diagram of an exemplary process forgenerating dynamic relationship-based content personalized for membersof a web-based social network is shown.

At step 505, at least one action of one or more members of web-basedsocial network 106 (FIG. 1) is stored. According to one embodiment,member action data may represent a particular member's actions on theweb-based social network 106 for a particular period of time.

At step 510, relationship data for the one or more members of theweb-based social network 106 is accessed. In one embodiment, arelationship database 204 (FIG. 2) stores data configured in memberprofiles, including friends and/or friends of friends of members.

At step 515, at least one action (step 505) is associated with therelationship data (step 510) to produce consolidated data. In oneembodiment, association component 302 associates a member's actions withthe member's friends and/or the member's friends of friends that mighthave also been involved with the same actions.

At step 520, one or more elements associated with the consolidated dataare identified. In one embodiment, an identification component 304identifies one or more symbols, sounds and/or images associated withconsolidated data.

At step 525, the consolidated data is aggregated based on the one ormore elements to produce aggregated consolidated data.

At step 530, the aggregated consolidated data is weighted by an affinityto generate dynamic relationship-based content personalized for themembers of the web-based social network 106. According to someembodiments, the content may be generated and/or ordered according to aprediction of future member activities.

At step 535, the generated dynamic relationship-based contentpersonalized for the members of the web-based social network 106 isstored.

At step 540, the stored generated dynamic relationship-based content ispublished for the members of the web-based social network 106. In oneembodiment, a server is configured to send the content to a member forwhom the content has been personalized.

While various embodiments have been described above, it should beunderstood that they have been presented by way of example only, and notlimitation. For example, any of the elements associated with the contentengine may employ any of the desired functionality set forthhereinabove. Thus, the breadth and scope of a preferred embodimentshould not be limited by any of the above-described exemplaryembodiments.

What is claimed is:
 1. A method comprising: accessing information abouta set of actions related to users of a social networking system, the setof actions sharing a common element; generating a unit of aggregatedsocial content for a viewing user, the aggregated social contentdescribing the common element, the set of actions, and users related tothe set of actions; determining affinity of the viewing user for theaggregated content and affinity of the viewing user for an additionalunit of social content; and providing for display, to the viewing user,the aggregated content and the additional social content, ordered withrespect to each other in accordance with the determined affinities. 2.The method of claim 1, wherein determining affinity of the viewing userfor the aggregated content comprises determining a numerical measure ofcombined interest of the viewing user in the common element, the set ofactions, and users related to the set of actions, the determination ofthe numerical measure performed by aggregating individual affinities ofthe viewing user for the combined element, for actions in the set, andfor the users related to the set of actions.
 3. The method of claim 1,wherein determining affinity of the viewing user for the aggregatedcontent comprises determining a likelihood that the viewing user wouldbe interested in at least a specified proportion of actions of the setof actions, the determination of the likelihood performed by aggregatingindividual affinities of the viewing user for actions in the set andidentifying a proportion of actions for which the individual affinityexceeds a specified affinity threshold.
 4. The method of claim 1,wherein determining affinity of the viewing user for the aggregatedcontent comprises determining a likelihood that the viewing user wouldbe interested in at least a specified proportion of users related to theset of actions, the determination of the likelihood performed byaggregating individual affinities of the viewing user for the usersrelated to the set of actions and identifying a proportion of users forwhich the individual affinity of the viewing user exceeds a specifiedaffinity threshold.
 5. The method of claim 1, wherein determiningaffinity of the viewing user for the aggregated content comprisesdetermining a measure of overlap between the set of actions sharing thecommon element and actions performed by the viewing user on web pagesexternal to the social networking system.
 6. The method of claim 1,wherein determining affinity of the viewing user for the aggregatedcontent comprises determining a measure of overlap between actionsperformed by the viewing user within the social networking system andthe set of actions sharing the common element.
 7. The method of claim 1,wherein determining affinity of the viewing user for the aggregatedcontent comprises determining a measure of overlap between the set ofactions sharing a common element and predicted actions for the viewinguser within the social networking system, the predicted actionsdetermined based on an extrapolation of social activity logged inassociation with the viewing user.
 8. The method of claim 1, whereindetermining affinity of the viewing user for the aggregated contentcomprises determining a measure of overlap between the set of actionssharing the common element and actions performed by social networkingusers having a direct friend connection with the viewing user.
 9. Themethod of claim 1, wherein accessing information about a set of actionsrelated to users of a social networking system comprises selectingactions that share the common element and that occurred within aspecified window of time from each other.
 10. The method of claim 1,wherein the set of actions share a common element based on having acommon action type.
 11. The method of claim 1, wherein the set ofactions share a common element by virtue of having been performed inconjunction with a common social networking system object.
 12. Themethod of claim 1, wherein the set of actions share a common element byvirtue of having been performed in conjunction with a common class ofmedia content items.
 13. The method of claim 1, wherein the set ofactions share a common element by virtue of having been performed byusers who share a common social profile attribute.
 14. The method ofclaim 1, wherein determining affinity of the viewing user for theadditional unit of social content comprises determining a numericallikelihood that the viewing user would have a propensity to beinterested in content to be displayed in conjunction with the additionalunit of social content.
 15. The method of claim 1, wherein: the unit ofaggregated social content is a consolidated social story that comprisesa single narrative description unifying the common element, the set ofactions, and users related to the set of actions; the additional unit ofsocial content is an additional social story that comprises a narrativedescription of a single action associated with a single socialnetworking system user sharing a direct friend connection with theviewing user; and wherein providing for display, to the viewing user,the aggregated content and the additional social content, ordered withrespect to each other in accordance with the determined affinitiescomprises ordering the consolidated social story and the additionalsocial story for spatial placement in a newsfeed of stories provided tothe viewing user, the ordering being based on the determined affinities.16. The method of claim 1, wherein generating a unit of aggregatedsocial content further comprises augmenting the aggregated socialcontent with audio or graphic content representative of the commonelement.
 17. A computer program product comprising a non-transitorycomputer-readable storage medium including instructions that, whenexecuted by a processor, cause the processor to: access informationabout a set of actions related to users of a social networking system,the set of actions sharing a common element; generate a unit ofaggregated social content for a viewing user, the aggregated socialcontent describing the common element, the set of actions, and usersrelated to the set of actions; determine affinity of the viewing userfor the aggregated content and affinity of the viewing user for anadditional unit of social content; and provide for display, to theviewing user, the aggregated content and the additional social content,ordered with respect to each other in accordance with the determinedaffinities.
 18. The computer program product of claim 17, wherein theinstructions that cause the processor to determine affinity of theviewing user for the aggregated content comprise instructions fordetermining a numerical measure of combined interest of the viewing userin the common element, the set of actions, and users related to the setof actions, the determination of the numerical measure performed byaggregating individual affinities of the viewing user for the combinedelement, for actions in the set, and for the users related to the set ofactions.
 19. The computer program product of claim 17, wherein theinstructions that cause the processor to access information about a setof actions related to users of a social networking system compriseinstructions for selecting actions that share the common element andthat occurred within a specified window of time from each other.
 20. Thecomputer program product of claim 17, wherein: the unit of aggregatedsocial content is a consolidated social story that comprises a singlenarrative description unifying the common element, the set of actions,and users related to the set of actions; the additional unit of socialcontent is an additional social story that comprises a narrativedescription of a single action associated with a single socialnetworking system user sharing a direct friend connection with theviewing user; and wherein instructions that cause the processor toprovide for display, to the viewing user, the aggregated content and theadditional social content, ordered with respect to each other inaccordance with the determined affinities, comprise instructions forordering the consolidated social story and the additional social storyfor spatial placement in a newsfeed of stories provided to the viewinguser, the ordering being based on the determined affinities.